{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 一、导入库\n",
    "在jupyter notebook中使用matplotlib绘图需要使用如下语句"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "x = np.linspace(-3,3,50)\n",
    "y1 = 2*x + 2\n",
    "y2 = x**2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 二、简单绘图\n",
    "\n",
    "`plt.figure()` - 申请一个图像窗口。可以输入参数编号num，和窗口大小figsize\n",
    "\n",
    "`plt.plot()` - 属性：颜色color，宽度linewidth，线型linestyle，标记marker，标记大小markersize\n",
    "\n",
    "`plt.show()` - 显示图形"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(num=1,figsize=(8,5))\n",
    "plt.plot(x,y1)\n",
    "plt.plot(x,y2,color='red',linewidth=2.0,linestyle='--')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 三、设置坐标\n",
    "## 1. 坐标轴样式\n",
    "\n",
    "`plt.xlim((a1,a2))` - 设置坐标轴范围\n",
    "\n",
    "`plt.xlabel('...')` - 设置坐标轴名称\n",
    "\n",
    "`plt.xticks()` - 设置刻度，传入列表作为刻度，也可以再传入对应刻度的名称\n",
    "\n",
    "> `plt.xticks(())` 可以取消刻度"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(7,5))\n",
    "plt.plot(x,y1)\n",
    "plt.plot(x,y2,color='red',linewidth=2.0,linestyle='--')\n",
    "# 设置坐标\n",
    "plt.xlim((-1,2.5))\n",
    "plt.ylim((-1,4))\n",
    "plt.xlabel('I am x',fontsize=16)\n",
    "plt.ylabel('I am y',fontsize=16)\n",
    "plt.xticks(np.linspace(-1,2.5,8))\n",
    "plt.yticks([-1, 0, 0.5, 2.5, 4],\n",
    "           [r'$really\\ bad$', r'$bad$', r'$normal$', r'$good$', r'$really\\ good$'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. 坐标轴颜色\n",
    "`axes = plt.gca()` - 获取当前坐标轴域信息\n",
    "\n",
    "`axes.spines['right']` - 获取右边的边框，类似的参数有left，top，bottom\n",
    "\n",
    "`axes.spines['right'].set_color('none')` - 设置边框颜色，none为无色\n",
    "\n",
    "## 3. 坐标轴和刻度位置\n",
    "`axes.spines['bottom'].set_position(('data',0))` - x轴在y=0的位置（位置所有属性：outward，axes，data）\n",
    "\n",
    "`axes.xaxis.set_ticks_position('bottom')` - x刻度在轴下方（所有位置：top，bottom，both，default，none）\n",
    "\n",
    "`axes.yaxis.set_ticks_position('left')` - y刻度在轴左方（所有位置：left，right，both，default，none）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,5))\n",
    "plt.plot(x,y1)\n",
    "plt.plot(x,y2,color='red',linewidth=2.0,linestyle='--')\n",
    "# 设置右上边框为空白\n",
    "axes = plt.gca()\n",
    "axes.spines['right'].set_color('none')\n",
    "axes.spines['top'].set_color('none')\n",
    "# 设置轴和刻度位置\n",
    "axes.spines['bottom'].set_position(('data', 0))\n",
    "axes.xaxis.set_ticks_position('top')\n",
    "axes.spines['left'].set_position(('data',0))\n",
    "axes.yaxis.set_ticks_position('left')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 四、Legend图例\n",
    "\n",
    "### 方法一： 在plot时设置，之后再设置位置\n",
    "`plt.plot(x,y,label='linear line')` - 在plot时传入参数`label=''`可设置图例\n",
    "\n",
    "`plt.legend(loc='upper right')` - 设置legend的位置\n",
    "\n",
    "### 方法二： 在plot后设置，plot时要保存返回值\n",
    "`plt.legend(handles=[l1,l2],labels=['up','down'])` - 在plot之后设置legend，其中`l1,l2`是plot函数的返回值\n",
    "\n",
    "> `loc`参数可选： 'best' : 0，'upper right'  : 1，\n",
    " 'upper left'   : 2，\n",
    " 'lower left'   : 3，\n",
    " 'lower right'  : 4，\n",
    " 'right'        : 5，\n",
    " 'center left'  : 6，\n",
    " 'center right' : 7，\n",
    " 'lower center' : 8，\n",
    " 'upper center' : 9，\n",
    " 'center'       : 10 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(7,5))\n",
    "# 在plot时设置图例\n",
    "# 注意l1要加逗号，因为plot返回的是一个列表\n",
    "l1, = plt.plot(x,y1)\n",
    "l2, = plt.plot(x,y2,color='red',linewidth=2.0,\n",
    "              linestyle='--')\n",
    "plt.legend(handles=[l1,l2],labels=['linear','square'], loc='best')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 五、Annotation标注\n",
    "### 1. plt.annotate()方法\n",
    "```\n",
    "plt.annotate(\n",
    "            r'$2x+1=%s$' % y0,  # 要标注的字符串\n",
    "            xy=(x0, y0), xycoords='data',  #要标注的点 \n",
    "            xytext=(+30, -30), textcoords='offset points', fontsize=16,  # 标注文字设置\n",
    "            arrowprops=dict(arrowstyle='->', connectionstyle=\"arc3,rad=.2\")  # 箭头设置\n",
    "            )\n",
    "```\n",
    "\n",
    "**参数：**\n",
    "\n",
    "`xy=(x0,y0)` - 表示箭头指向的坐标\n",
    "\n",
    "`xycoords='data'` - `xy`使用坐标的值来表示坐标\n",
    "\n",
    "`textcoords='offset points'` - 文字的位置相对于标注的点\n",
    "\n",
    "`xytext=(30,-30)` - 文字的位置\n",
    "\n",
    "`arrowprops` - 箭头属性\n",
    "\n",
    "### 2. plt.text()添加注释\n",
    "\n",
    "```\n",
    "plt.text(-3.7, 3, r\"$it's\\ text.\\mu\\ \\alpha_t$\",\n",
    "         fontdict={'size': 16, 'color': 'r'})\n",
    "```\n",
    "**参数：**\n",
    "\n",
    "`-3.7, 3`是text左上角的坐标，字符串中空格需要用到转义字符`\\`，`fontdict`设置文本字体."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(x,y1)\n",
    "x0 = 0\n",
    "y0 = 2*x0 + 2\n",
    "# 画出标注的点\n",
    "plt.scatter([x0, ], [y0, ], s=50, color='b')\n",
    "# annotate标注\n",
    "plt.annotate(r'$2x+2=y$', xy=(x0, y0), xycoords='data', xytext=(+30, -30),\n",
    "             textcoords='offset points', fontsize=16,\n",
    "             arrowprops=dict(arrowstyle='->', connectionstyle=\"arc3,rad=.2\"))\n",
    "# text标注\n",
    "plt.text(-2, 3, r\"$it's\\ text.\\mu\\ \\alpha_t$\",\n",
    "         fontdict={'size': 16, 'color': 'r'})\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [default]",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
